The present invention relates generally to the field of medical imaging. In particular, the following techniques relate to computed tomography imaging systems and the calibration of detectors used in such systems.
Computed tomography (CT) imaging systems measure the intensity of X-ray beams passed through a patient from numerous angles. With sufficient angular coverage around the patient, cross-sectional images can be formed, revealing the inner structure of the scanned object. The images are typically displayed on a cathode ray tube, and may be printed or reproduced on film. A virtual 3-D image may also be produced by a CT examination.
CT scanners operate by projecting fan shaped or cone shaped X-ray beams from an X-ray source that is collimated and passes through the object, such as a patient. The attenuated beams are then detected by a set of detector elements. The detector element produces a signal based on the intensity of the X-ray beams. The measured data are then processed to represent the line integrals of the attenuation coefficients of the object along the ray paths. The processed data are typically called projections. By using reconstruction techniques, such as filtered backprojection, cross-sectional images are formulated from the projections. The locations of pathologies may then be identified either automatically, such as by a computer-assisted diagnosis (CAD) algorithm or, more conventionally, by a trained radiologist. CT scanning provides certain advantages over other types of techniques in diagnosing disease particularly because it illustrates the accurate anatomical information about the body. Further, CT scans may help physicians distinguish between types of abnormalities more accurately.
To obtain accurate CT images, a number of calibration and correction algorithms may be applied. One such calibration is spectral calibration. The spectral calibration process generally employs calibration phantoms composed of materials such as water or plastic, which presumably attenuate X-rays passing through the phantom in a manner similar to soft tissue. The respective spectral response of each detector channel is then determined and a correction factor for each detector channel is generated to normalize the respective spectral responses.
In general, the spectral calibration addresses sources of spectral error, i.e., errors arising from changes of the X-ray spectrum. For instance, one example of spectral error may be X-ray beam hardening, also known as “cupping,” which manifests as non-uniformities in the imaged water or soft tissue. In particular, because X-ray attenuation coefficients are a function of X-ray photon energy, the polychromatic nature of the X-rays generated by an X-ray tube may lead to spectral errors which are observed as X-ray beam hardening.
Another source of spectral error, however, arises due to the variation in detector efficiency between the detectors comprising the detector array. For example, detector efficiency variations within an array may generate bone-induced spectral (BIS) image artifacts in images of body parts in which there is a mixture of both soft tissue and bone, such as in head images. The BIS artifacts are typically manifested as a ring or band in the reconstructed image. The source of the BIS artifact is complex, and any imperfection of the imaging system, such as in the detector or the anti-scatter collimator, may contribute to the incidence of BIS artifacts. In particular, the BIS artifacts may be observed when there are discrepancies between the observed and the expected spectral response by the detector, such as when the spectral content incident upon the detector elements is changed due to the presence of bone.
Removal of the BIS artifacts may be problematic even the system has undergone a successful spectral calibration because the derived spectral correction factors are generally useful for correcting image artifacts in regions of water or soft tissue, not bone. Indeed, the BIS artifact typically does not appear in images of test-phantoms, which are made of water-like materials. Furthermore, the correction employed to minimize beam hardening artifacts in the presence of bones, such as in head images, merely functions to remove streaking and to sharpen the boundary between bone and soft tissue in the images. The correction, however, does not account for the spectral response discrepancies between detector elements introduced by bone and, therefore, does not correct BIS artifacts.
Indeed, in general, BIS artifacts are neither characterized nor addressed by a specific calibration or correction procedure. Instead, a detector array may be configured to ensure similar spectral response of the detector channels which image at or near the isocenter of the imaging volume. This approach may involve physically swapping detector modules such that higher quality or similarly spectrally responsive modules are positioned in the portion of the detector that samples rays of the isocenter region. In addition to the rather arbitrary nature of this approach, the module swapping process is time consuming and cannot be relied upon to generate consistent results between detectors. Further, with the development volumetric CT, the swapping process is more difficult, simply due to the increased number of channels in the detector module. A fast, reproducible, and reliable technique for correcting BIS artifacts in reconstructed images is therefore desirable.